Mining and identification of solitary long terminal repeat (Solo-LTR) presence polymorphisms in the sheep genomes
Bibliographic record
Abstract
The analysis of 51 sheep genomes led to the identification of 3624 high-confidence Solitary Long Terminal Repeats (Solo-LTRs), remnants of Long Terminal Repeat retrotransposons (LTR-RTns). These elements, comprising 3308 absence-type and 316 presence-type sites, are integrated into functional regions of the genome, where they can influence gene structures and regulation. Approximately 4.39% of protein-coding genes and 0.54% of long noncoding RNA genes contain sequences derived from these Solo-LTRs. Analysis across 12 diverse sheep breeds revealed that 83.63% of the tested Solo-LTR sites were polymorphic, demonstrating substantial genetic diversity and highlighting their utility as genetic markers. Furthermore, these elements were linked to key genes governing economically important traits such as growth, immunity, and milk production. Notable genes identified include PAG3, ANXA5, KCNJ6, MX2, and XKR4. The findings confirm that Solo-LTRs are major contributors to genomic diversity and breed-specific adaptation in sheep, providing essential insights for future genetic research and breeding programs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".